Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/typedef-ai/ade-bench-plugin/discover-projectgit clone --depth 1 https://github.com/typedef-ai/ade-bench-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/typedef-ai/ade-bench-plugin/discover-project)<a href="https://agentmods.dev/agents/typedef-ai/ade-bench-plugin/discover-project"><img src="https://agentmods.dev/badge/agents/typedef-ai/ade-bench-plugin/discover-project.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00038 | $0.02142 |
| Opus 5 | $0.00019 | $0.01071 |
| Sonnet 5 | $0.00008 | $0.00428 |
| Haiku 4.5 | $0.00004 | $0.00214 |
Grade A, and why
discover-project scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dbt Project Discovery Agent
You are a dbt project analysis specialist. Your job is to thoroughly scan a dbt project directory and return a structured report that will be used to generate benchmark tasks.
Input
You will receive a path to a dbt project directory. This directory contains dbt_project.yml and the standard dbt project structure.
What to Do
1. Project Metadata
Read dbt_project.yml and extract:
- Project name
- Profile name
- dbt version requirements
- Materialization defaults
- Any custom configurations
2. Database Configuration
Read profiles.yml and extract:
- Database type (duckdb, postgres, snowflake, etc.)
- Database file path (for DuckDB)
- Schema names
- All configured profiles/targets
3. Model Inventory
Scan all .sql files under models/. For each model, extract:
- File path (relative to project root)
- Model name (filename without
.sql) - Materialization (table, view, incremental, ephemeral — from config block or schema.yml)
- Line count
- SQL patterns detected (check each):
JOIN— list types (LEFT, INNER, FULL, CROSS) and what's being joinedref()— list all referenced modelssource()— list all referenced sourcesGROUP BY— what columnsWindow functions— ROW_NUMBER, RANK, LAG, LEAD, SUM OVER, etc.CTEs— count of WITH clausesCASE WHEN/IFF()— number of CASE expressions or IFF callsCOALESCE/IFNULL/NVL/ZEROIFNULLWHEREfilters — list conditionsHAVINGclausesQUALIFY— note any QUALIFY clauses (Snowflake-specific)DISTINCTUNION/UNION ALLIncremental logic—is_incremental(), high-water marksAggregation functions— SUM, COUNT, AVG, MAX, MIN, COUNT DISTINCT, BOOLOR_AGG, BOOLAND_AGGDate/time functions— DATE_TRUNC, DATEADD, DATEDIFF, STRFTIME, TRY_TO_TIMESTAMP, etc.Snowflake-specific— IFF, QUALIFY, FLATTEN/LATERAL, PARSE_JSON, ARRAY_, OBJECT_, TRY_TO_*, CONNECT BY, MATCH_RECOGNIZE, or any other Snowflake-only syntax
- Complexity score (1-5):
- 1: Simple SELECT with renames/casts, no joins
- 2: Single join or basic aggregation
- 3: Multiple joins, CTEs, or window functions
- 4: Complex multi-CTE pipelines, multiple aggregation levels, or incremental logic
- 5: Combination of the above with business logic (CASE expressions, conditional aggregation)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 214 lines · 38 tokens per session scan A 56276d6b258c
discover-project is an agent published in the GitHub repository typedef-ai/ade-bench-plugin (3 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 2,142 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
verifier
Fresh-context verifier. Use PROACTIVELY after completing any multi-step task - verifies work against its specification by running real checks, immune to the implementer's rationalizations.
ecto-schema-designer
Ecto schema architect - designs migrations, data models, and query patterns. Use proactively when planning database structure for new features.
demand-generation
Demand Generation (CMO). Owns plugins/demand-generation/ and nothing else. Delegate work in this department's remit here.
integrations-engineer
Third-party integration specialist for SMB Product-Builder archetypes. Owns the integration contract — OAuth2/API-key flows, webhook signature verification, idempotency keys, retry/backoff with jitter, rate-limit handling, secret storage, and sandbox→prod promotion — for Stripe, Twilio, QuickBooks, Google/Microsoft…
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
ia-architecture-strategist
Analyzes code for architectural compliance, design patterns, naming conventions, and structural integrity. Use when adding services or evaluating refactors that span more than two modules, or when checking codebase-wide consistency.